Lidar detection systems and methods with high repetition rate to observe far objects

ABSTRACT

Embodiments discussed herein refer to LiDAR systems that accurately observe objects that are relatively close and objects that are relatively far using systems and methods that employ a variable time interval between successive laser pulses and one or more filters.

CROSS-REFERENCE TO A RELATED APPLICATION

This application claims the benefit of U.S. Provisional Application No.62/633,348, filed Feb. 21, 2018, the disclosure of which is incorporatedherein in its entirety.

FIELD OF THE INVENTION

The present disclosure relates to light detection and ranging (LiDAR),and in particular to LiDAR systems and methods for use in a vehicle.

BACKGROUND

Systems exist that enable vehicles to be driven semi-autonomously orfully autonomously. Such systems may use one or more range finding,mapping, or object detection systems to provide sensory input to assistin semi-autonomous or fully autonomous vehicle control. ConventionalLiDAR systems designed to observe objects 200 meters or more away use arelatively slow repetition rate. The relatively slow repetition rateresults in a relatively low resolution, but does not result in too manyfalse positives. However, in order to improve the resolution,conventional LiDAR systems may increase its repetition rate. Theincrease in repetition rate, however, results in false alarms. This isbecause an object that is relatively far away is registered as an objectthat is relatively close. This is so called “range ambiguity”. Sucherroneous false positives may adversely affect the operation of avehicle using this conventional LiDAR system.

It is desirable for LiDAR systems to accurately observe objects,including objects that are close and objects that are far.

BRIEF SUMMARY

Embodiments discussed herein refer to LiDAR systems that accuratelyobserve objects that are relatively close and objects that arerelatively far using systems and methods that employ a variable highfrequency repetition rate and a filter or multiple filters.

In one embodiment, a light detection and ranging (LiDAR) system isprovided. The LiDAR system can include a transmission system, which caninclude a laser, time interval adjustment circuitry operative togenerate a variable time intervals, and transmission control circuitrycoupled to the laser and the time interval adjustment circuitry, whereinthe control circuitry is operative to cause the laser to emittransmission pulses in accordance with the variable time intervals. Thesystem can include a receiver system having a receiver operative todetect return pulses that are consequences of the transmission pulses,and receiver control circuitry coupled to receive an output of thereceiver and the variable time interval. The receiver control circuitrycan be operative to: for each detected return pulse, calculate aplurality of object distances based on a plurality of successivetransmission pulses; compare at least two calculated object distancescorresponding to a currently detected return pulse to at least twocalculated distance objects corresponding to a previously detectedreturn pulse to filter out calculated distance objects that fail filtercriteria; and provide object distances that pass the filter criteria asdata points for constructing an image of objects observed by the LiDARsystem.

In another embodiment, a method for using a LiDAR system to generate animage of observed objects is provided. The method includes transmittingsuccessive transmission pulses in accordance with a variable timeinterval, wherein the variable time interval changes for eachtransmission pulse, receiving a plurality of return pulses, in responseto each received return pulse, calculating a plurality of objectdistances based on a plurality of successive transmission pulses,comparing at least two calculated object distances corresponding to acurrently detected return pulse to at least two calculated distanceobjects corresponding to a previously detected return pulse to filterout calculated distance objects that fail filter criteria, rejectingobject distances that fail filter criteria, and providing objectdistances that pass filter criteria for use in generating the image.

In another embodiment, a LiDAR system is provided that includes a lasertransmission system operative to transmit laser pulses in succession,wherein a time interval between successively transmitted laser pulses isvaried, a receiver system to detect return pulses that are consequencesof the transmitted laser pulses, and control circuitry operative to usethe varied time interval of successively transmitted laser pulses todiscriminate among distance calculations of an object corresponding tothe return pulses.

In another embodiment, a method for using a LiDAR system is providedtransmitting successive transmission pulses in accordance with avariable time interval, wherein the variable time interval changes foreach transmission pulse; receiving a plurality of return pulsescorresponding to an object; determining distance calculationscorresponding to the object based on the plurality of return pulses anda plurality of successive transmission pulses; discriminating among thedistance calculations by evaluating the plurality of return pulses inconnection with the variable time interval of the successivetransmission pulses; and providing the discriminated distances as datapoints for generating a image representing a field of view of the LiDARsystem.

In yet another embodiment, a method for using a LiDAR system provided bydiscriminating among observed objects that are relatively close andobserved objects that are relatively far by varying a time intervalbetween successive laser pulses being emitted by the LiDAR system, andusing results of the discriminating as data points for generating aimage representing a field of view of the LiDAR system.

A further understanding of the nature and advantages of the embodimentsdiscussed herein may be realized by reference to the remaining portionsof the specification and the drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows an illustrative scenario in which a conventional LiDARsystem can detect objects but is unable to distinguish distancedifference between multiple objects;

FIG. 2 shows an illustrative timing diagram;

FIG. 3A shows an illustrative LiDAR system, according to an embodiment;

FIG. 3B shows an illustrative laser pulse pattern, according to anembodiment;

FIG. 4 shows illustrative block diagram of a portion of the LiDAR systemof FIG. 3, according to an embodiment;

FIG. 5 shows an illustrative timing diagram showing transmission pulsesand corresponding time stamps and receiver pulses and corresponding timestamps, according to an embodiment;

FIG. 6 shows object distances, according to an embodiment;

FIGS. 7A and 7B show illustrative applications of filtering criteria,according to various embodiments;

FIG. 8 shows an illustrative process that uses a varying repetition rateto produce filtered distance objects in accordance with variousembodiments; and

FIG. 9 is a functional block diagram illustrating a vehicle system,according to an embodiment.

DETAILED DESCRIPTION

Illustrative embodiments are now described more fully hereinafter withreference to the accompanying drawings, in which representative examplesare shown. Indeed, the disclosed LiDAR systems and methods may beembodied in many different forms and should not be construed as limitedto the embodiments set forth herein. Like numbers refer to like elementsthroughout.

In the following detailed description, for purposes of explanation,numerous specific details are set forth to provide a thoroughunderstanding of the various embodiments. Those of ordinary skill in theart will realize that these various embodiments are illustrative onlyand are not intended to be limiting in any way. Other embodiments willreadily suggest themselves to such skilled persons having the benefit ofthis disclosure.

In addition, for clarity purposes, not all of the routine features ofthe embodiments described herein are shown or described. One of ordinaryskill in the art would readily appreciate that in the development of anysuch actual embodiment, numerous embodiment-specific decisions may berequired to achieve specific design objectives. These design objectiveswill vary from one embodiment to another and from one developer toanother. Moreover, it will be appreciated that such a development effortmight be complex and time-consuming but would nevertheless be a routineengineering undertaking for those of ordinary skill in the art havingthe benefit of this disclosure.

FIG. 1 shows an illustrative scenario in which a conventional LiDARsystem can detect objects but is unable to distinguish distancedifference between multiple objects. In particular, FIG. 1 shows LiDARsystem 100, which can include transmitter 104 and receiver 106, nearobject 130, and far object 140. Far object is farther away from system100 than near object 130. During operation, transmitter 104 transmitssignal T1 first, followed by signal T2. Each transmitted signal producesa receiver signal when the transmitted signal reflects back from anobject. Receiver signal R1 is produced in response to transmit signalT1, and receiver signal R2 is produced in response to transmit signalT2. Receiver 106 may receive signal R2 before it receives signal R1,even though signal T1 was transmitted before signal T2. Receipt ofsignal R2 before R1 may cause system confusion of the correctcorrespondence of transmitted and received signals, thus calculate thedistance incorrectly. In order to prevent confusion, the repetition rateof transmitter pulses (or signals) is slowed down, so that the timeinterval between T1 and T2 is large enough that R1 can return before thesystem sends T2. In practice this time interval is set to be the roundtrip time of light traveling in the maximum detection distance withoptional additional margin. However, a relatively slow repetition rateresults in a relatively low resolution. To increase the resolution, ahigh repetition rate system is required. Increasing the repetition rate,M, effectively limits how far system 100 can accurately observe objects.The distance of an observed object is equal to c/2/M, where c is thespeed of light, and M is the repetition rate of the transmitter pulses.

FIG. 2 shows an illustrative timing diagram of a transmitter havingtransmitter signals T1 and T2, and of a receiver having receiver signalR1. As shown, transmitter signal T1 is transmitted at time, t_(T1), andtransmitter signal T2 is transmitted at time, t_(T2), and receiversignal R1 is received at time, t_(R1). A conventional LiDAR system has afixed repetition rate, M. The time interval between each transmitterpulse is 1/M. For example, if the repetition rate is 1 MHz, then thetime interval is 1 μs. Based on a distance equation of c/2/M, a 1 Mhzrepetition results in a distance of 150 meters. If the object is locatedat a distance greater than 150 meters, such as 180 meters, the receiversignal R1 is received at time that exceeds the 1 μs time interval (i.e.,1.2 μs after time, tri, and 0.2 μs after time, tr. The system cannotdistinguish whether R1 is the return pulse corresponding to T1 or T2.Conventional systems may typically consider that R1 is a returncorresponding to T2 (e.g., because objects that are relatively far awaytypically have weak return signals). In considering that R1 correspondsto T2, the system may determine the object is (1.2-1.0 μs)*c/2 is 30meters. In this regard, R1 is considered a ghost because an object thatis actually far away is being considered as an object that is close.Registering the object at meters instead of 180 meters may result inundesired actions (e.g., an erroneous brake by an autonomous carsystem). As defined herein, a ghost object is associated with theincorrect distance calculation. Referring to the example above, R1 isactually at 180 meters, but the system also registers R1 at 30 meters.Embodiments discussed herein are able to reject the 30 meter distancecalculation as a ghost image and use 180 meters as the correct distancecalculation to be assigned to R1.

Embodiments discussed herein vary the time interval between eachtransmitter pulse. Time interval variation of successive pulses enablesthe LiDAR system and methods for the use thereof to accurately detectobjects that are observed relatively far away, reject ghost, and avoidinterference from other LiDAR systems.

FIG. 3A shows an illustrative LiDAR system 300 according to anembodiment. System 300 can include transmitter system 310 and receiversystem 350. Other components and systems may exist as part of the LiDARsystem 300, but are not shown to avoid overcrowding the drawing.Transmitter system 310 can include clock 312, repetition rate/timeinterval adjustment circuitry 320, control circuitry 330, and laser 340.Clock 312 may be a system clock that serves as a reference for one ormore components in system 300. Time interval adjustment circuitry 320may be operative to control and/or adjust the repetition rate/timeinterval of the transmitter pulse of laser 340. Time interval adjustmentcircuitry 320 can vary the repetition rate/time interval for eachtransmitter pulse such that no two successive transmitter pulses havethe same repetition rate/time interval. For example, assume that a firstinterval between a first transmitter pulse and a second transmitterpulse is M, then the immediately successive interval for a successivetransmitter pulse is (1±α)M, where α is a randomization factor that isapplied to M. The randomization factor may be bounded to prevent thetime interval from exceeding maximum and minimum bounds

Control circuitry 330 may receive the repetition rate from repetitionrate adjustment circuitry for each transmitter pulse and causes laser340 transmit laser pulses in accordance with the current repetitionrate. For example, for a first period, the time interval betweensuccessive pulses may be 1 us, then for a third successive pulse (whichimmediately follows the first two pulses), the time interval may be 1.1us, and then for a fourth successive pulse, the time interval may be0.97 us. The laser pulses being emitted by laser 340 may be directedthrough scanning and receiving optics 345, which may include acombination of lenses, mirrors, one or more rotating polygons and/oroscillation mirrors, and any other suitable components. See, forexample, commonly assigned U.S. patent application Ser. No. 16/242,567,filed Jan. 8, 2019, for illustrative examples of scanning and receivingoptics.

Receiver system 350 can include receiver 352, control circuitry 360, andimaging system 380. Receiver 352 may detect return pulses originatingfrom transmission pulses that are reflected back from one or moreobjects. Reflected transmission pulses may be routed through a portionof scanning and receiving optics 345 to receiver 352. Control circuitry360 may receive the time stamp of when the system fires a laser pulsefrom repetition rate/time interval adjustment circuitry 320 andoperative to apply analytics and noise rejection to the data obtained byreceiver 352 to provide filtered results. The filtered results may beprovided to imaging system 380. Imaging system 380 may construct a 2D or3D image of the environment being scanned by LiDAR system 300. Duringthis process, reference beam information can be applied to the system todetermine precise time stamps for receiving pulses and transmittingpulses as well.

FIG. 3B shows an illustrative laser pulse pattern that may be providedby LiDAR system 300, according to an embodiment. LiDAR system 300 mayproject an array of laser pulses 390 that enables system 300 to observea space (e.g., a two or three dimensional space). This array of laserpulses is projected every image capture cycle. Objects within the spacecan return laser pulses back to the system 300, which receives thereturn pulses and uses the data points to construct an image of objectswithin the space. The methods and algorithms for transmitting the laserpulses and how the data is interpreted is the subject of manyembodiments discussed herein. LiDAR system 300 may be designed toobserve a lateral field of view for each angle along a vertical field ofview. The angles of the vertical field of view are shown as P0, P1, P2,through PN, and the lateral fields of view are shown as the sequence ofdashed lines corresponding to each angle of the vertical field of view.At angle P0, for example, a laser pulse is transmitted at each dashedline, shown specifically at times T1 ₀, T2 ₀, T3 ₀, T4 ₀ through TN₀.The 0 subscript corresponds to the P0 angle. Similarly, at angle P1, alaser pulse is transmitted at times T1 ₁, T2 ₁, T3 ₁, T4 ₁ through TN₁.The 1 subscript corresponds to the P1 angle. Laser pulses aretransmitted at each of the times as shown for all angles. The imagecapture cycle may include one sweep of all transmitted laser pulses forall angles. For example, the image capture cycle may start at time T1 ₀and end at time TN_(N).

The time interval between each laser pulse is varied in both the timeand space. Time variations refer to variations in the time intervalbetween laser pulses between each pulse across the lateral field of viewis different. That is, the time interval between time T1 ₀ and T2 ₀ isdifferent than the time interval between T2 ₀ and T3 ₀, and the timeinterval between T2 ₀ and T3 ₀ is different than the time intervalbetween T3 ₀ and T4 ₀, and so on. Space variations refer to variationsin the time interval of laser pulses between adjacent angles. That is,the time interval between time T1 ₀ and T2 ₀ is different than the timeinterval between T1 ₁ and T2 ₁, and the time interval between T2 ₀ andT3 ₀ is different than the time interval between T2 ₁ and T3 ₁, and soon. Moreover, the time interval between time T1 ₁ and T2 ₁ is differentthan the time interval between T1 ₂ and T2 ₂. Control circuitry 330 isaware of the time interval of each laser pulse and can ensure that thetime interval varies across and time and space.

FIG. 4 shows an illustrative object rejection module 400 that may beexecuted by control circuitry 360 to confirm the distance accuracy ofobjects detected by receiver 352. Module 400 may be a software programthat is executed by control circuitry 360 to verify the existence ofobjects at particular distances when LiDAR system 300 is operating atmuch high repetition rates than those of conventional LiDAR systems.Object rejection module 400 can include object distance calculationmodule 410, object filter module 420, and filtered distance objects 430.Object rejection module 400 is able to accurately determine the distanceof an object by taking into account the varying time intervals and byapplying one or more filters to reject distance calculations that do notmeet the appropriate criteria.

Object distance calculation module 410 may receive the time intervalfrom circuitry 320 and outputs from receiver 352, and based on thoseinputs, it can calculate several different distances, each correspondingto different transmission time stamps. That is, module 410 can calculatethe distance of the detected object with respect to the currenttransmission time stamp, the distance of the detected object withrespect to the previous transmission time stamp, and if desired, thedistance of the detected object with respect to any number oftransmission time stamps immediately preceding the previous transmissiontime stamp. The transmission time stamp coincides with when laser 340 isinstructed to emit a laser pulse. Since laser 340 emits a laser pulsebased on a variable time interval, module 410 may maintain a movingwindow of distance calculations (with respect to multiple transmissiontime stamps) for at least two successive receiver signals. To furtherillustrate this concept, please refer now to FIGS. 5 and 6.

FIG. 5 shows an illustrative timing diagram showing transmission pulsesand corresponding time stamps and receiver pulses and corresponding timestamps. The transmission pulses are shown as T₁, T₂, T₃, and T₄, and thereceiver pulses are shown as R₁, R₂, and R₃. The timestamps for thetransmission pulses are shown as t_(T1) . . . t_(T4) and the timestampsfor receiver pulses are shown as t_(R1) . . . t_(R4). The time intervalsin between each transmission pulse are shown as M1, M2, and M3, whereM1≠M2 and M2≠M3 and are representative of the varying repetition ratefor each successive transmission pulse. The transmission pulses maycorrespond to transmission pulses corresponding to a particular angle(e.g., one of angles P0, P1, P2, through PN of FIG. 3B).

FIG. 6 shows object distances (OD) calculated for R1 and for R₂. Becausethe system does not know whether R1 corresponds to T2 or to T1, objectdistance calculation module 410 can calculate two different distances:one with respect to T2 (shown as OD1 _((R1))) and the other with respectto T1 (shown as OD2 _((R1))). As an example, assuming that t_(R1) is 1.2μs and M1 is 1 μs, OD1 _((R1)) is 30 meters and OD2 _((R1)) is 180meters. Because the system does not know whether R2 corresponds to T3 orto T2, object distance calculation module 410 can calculate twodifferent distances: one with respect to T3 (shown as OD1 _((R2))) andthe other with respect to T2 (shown as OD2 _((R2))). Following theexample above, and assuming that t_(R2) is 2.2 μs and M2 is 1.2 μs, OD1_((R2)) is 13.5 meters and OD2 _((R2)) is 180 meters.

Referring now back to FIG. 4, after the object distances calculation arecomplete, object filter module 420 can apply filter criteria todetermine whether to reject one or both of distance objects OD1 and OD2.The filter criteria is based on the fact that the object is continuousin the space, and the angle between the line connecting the consecutivescanning points landing on the object surface and the laser beam isgreater than a threshold. The latter criteria are valid because if thisangle is too small, the scattered light (return light) will be very weakdue to large incidence angle. If LiDAR system observed a positive returnfrom an object at a given angle, at least one of its neighbor anglesshould give a positive return as well. For example, referring briefly toFIG. 3B, if an object is detected at T2 ₁ and not detected at T1 ₁, T3 ₁or T2 ₀, that same object should be detected at T2 ₂. In addition, thedistance measured for these two neighbor positive returns should be lessthan a certain distance (e.g. 5 meters), assuming that no object canmove faster than a certain speed (e.g. 5 km/s) and the neighboringpoints are measured at a very short time interval (e.g. 1 us forscanning in the lateral direction, or 1 ms for scanning in the verticaldirection). If only one positive return is obtained and none of itsneighbor angles generates returns, the system considers it as a noise orfalse return. For example, referring again briefly to FIG. 3B, if areturn is seen at T2 ₁, but nothing within a reasonable distance (e.g. 5meters) is seen at T1 ₁, T3 ₁, T2 ₀, or T2 ₂, the system may reject thereturn at T3 ₁ as noise or a false return.

Referring now to FIG. 7A, object filter module 420 can apply atime-based filter by comparing object distances within the same angle.In particular, object filter module 420 can determine whether theabsolute value of the difference between OD1 _((R2)) and OD1 _((R1)) isless than a threshold (e.g. 5 meters). If that determination is true,the distance associated with OD1 is considered positive and is passed asa filtered distance object 430. If that determination is false, thedistance associated with OD1 is negative and that distance is stored inmemory. The negative OD1 is labeled as NOD1 and stored in memory forsubsequent higher level analysis. Object filter module 420 alsodetermines whether the absolute value of the difference between OD2_((R2)) and OD2 _((R1)) is less than the same threshold. If thatdetermination is true, the distance associated with OD2 is consideredpositive and is passed as a filtered distance object 430. If thatdetermination is false, the distance associated with OD2 is negative andthat distance is stored in the memory (and will be referred to below asNOD2). NOD1 and NOD2 can be used in a secondary verification to verifywhether the returns seen at NOD1 and NOD2 are valid. For example, NOD1and NOD2 can be applied to a space-based filter, described below toverify whether the returns seen at NOD1 and NOD2 are valid. Thespace-based filter can compare NOD1 and NOD2 to corresponding objectdistances at different vertical angles to determine whether anycorroborating returns exist at adjacent vertical angles. If nocorroborating returns exist for NOD1 and NOD2 at adjacent angles, thenNOD1 and NOD2 can be rejected. If corroborating returns exist for NOD1and NOD2 at adjacent angles, then NOD1 and NOD2 may be retained inmemory for further analysis. The vertical angles refer to angles withinthe vertical field of view of a LiDAR system.

As a continuation of the above example, if the threshold is 5 meters,then the OD1 filter would fail because 30-13.5 is 16.5, which is greaterthan 5, but the OD2 filter would pass because 180-180 is 0, which isless than 5. In reality, this number may be a small non-zero number,such as, for example, one to five centimeters depending on themeasurement uncertainty and movement of the object and LiDAR. Based onthis filter, OD1 would be rejected, and stored in the memory, and OD2distance of 180 meters would be passed as a filtered positive distanceobject 430.

Thus, it is shown that by varying the time intervals, the distance offar objects can be precisely calculated and mapped. This is because eventhough the far objects may cause ambiguities (e.g., ghosts) indetermining which return signal belongs to which transmitter pulse, thevariance of the repetition rate/time interval produces distancecalculations that enable the erroneous distances objects to be rejected.The time interval variation between the neighboring transmitter pulsesshould be sufficiently different to guarantee the filter criteria can beapplied to the system. For example, assume that a first time intervalfor a first transmitter pulse is M, then the immediately successive timeinterval for a successive transmitter pulse is (1±α)M, where α is arandomization factor that is applied to M. The randomization factor αshould be larger than a certain value, e.g. 0.02 for the filter criteriaof 5 meters and a time interval of 1 μs. The randomization factor andtime intervals should also be bounded to a maximum and minimum value toguarantee high resolutions. Thus, the difference in adjacent timeintervals is sufficiently different to ensure that “ghost” objects arefiltered out by the time-based filter.

In some embodiments, the time intervals can repeat as a sequence ofpredetermined time intervals. For example, the sequence can include afixed number of time intervals, each of which has a different lengththat satisfies a minimum delta requirement among adjacent time intervalsto account for various tolerances in the system. The sequence can berepeated as necessary to trigger transmission pulses in accordance withthe variable time intervals as discussed herein.

Referring now to FIG. 7B, object filter module 420 can apply aspace-based filter by comparing object distances between adjacentangles. For example, assume that the space-time filter produced NOD2according to a first angle (e.g., angle P0) and NOD2 according to anadjacent angle (e.g., angle P1). Object filter module 420 can determinewhether the absolute value of the difference between NOD2 _((P0)) andNOD2 _((P1)) is less than a vertical distance threshold. If thatdetermination is true, the distance associated with NOD2 is consideredaccurate and is passed as a filtered distance object 430. If thatdetermination is false, the distance associated with NOD2 is negativeand that distance is restored in the memory for higher level judgement.

In some embodiments, varying time interval can be used to detect objectsthat are really far away. This can be accomplished by calculating andfiltering object distances with respect to at least three successivetransmission pulses. For example, referring to FIG. 5, assume that R2 isactually a return corresponding to the T1 transmission pulse and that R3corresponds to the T2 transmission pulse, and R1 does not exist. Thesystem can determine whether R2 corresponds to T3, T2, or T1 usingembodiments discussed herein. In this example, object distancecalculation module 410 can calculate multiple object distances withrespect to R3 and R2 to determine the correct distance of R2. Forexample, module 410 can calculate the following object distance for R3:one with respect to T4 (OD1 _((R3))), one with respect to T3 (OD2_((R3))), and one with respect to T2 (OD3 _((R3))). Module 410 cancalculate the following object distance for R2: one with respect to T3(OD1 _((R2))), one with respect to T2 (OD2 _((R2))), and one withrespect to T1 (OD33 _((R2))). All of the object distances can beevaluated by one or more filters to determine which object distancesshould be accepted or rejected. For example, the OD1 filter cancalculate the difference between (OD1 _((R3))) and (OD1 _((R2))) andcompare it to a threshold, the OD2 filter can calculate the differencebetween (OD2 _((R3))) and (OD2 _((R2))) and compare it to the threshold,and the OD3 filter can calculate the difference between (OD3 _((R3)))and (OD3 _((R2))) and compare it to the threshold. In this particularexample, the difference between (OD3 _((R3))) and (OD3 _((R2))) isapproximately zero, thus indicating that the correct distance associatedwith R2 is correlated to transmission T1.

Thus, it should be appreciated that the variable time intervalembodiments can be used to correctly determine the location of objectsat any reasonable distance, including, for example, distances of 500meters or more. Depending on the desired range of distance calculations,the system can calculate the requisite number of distance calculationsneeded to make the determination. The example above showed the systemcalculating distance calculations with respect to three successivetransmission pulses (and FIG. 6 and FIG. 7A examples showed distancecalculations with respect to two successive transmission pulses). Ifdesired, the system can calculate distances with respect to any numberof successive transmission pulses, using the number necessary to coverthe desired range of object detection.

FIG. 8 shows an illustrative process 800 that uses a varying repetitionrate/time interval to produce filtered distance objects in accordancewith various embodiments. At step 810, for each received signal, severalobject distances are calculated based on a plurality of successivetransmission pulses, wherein a time interval varies between eachtransmission pulse of the plurality of transmission pulses. At step 820,at least two calculated object distances corresponding to a currentreceived signal are compared to at least two calculated object distancescorresponding to a previous received signal to filter out calculatedobject distances that fail filter criteria. At step 830, objectdistances that fail filter criteria are stored in memory for higherlevel analysis. At step 840, object distances that pass filter criteriaare passed to an imaging system.

It should be understood that the steps in FIG. 8 are merely illustrativeand that additional steps may be added and the order to the steps may berearranged.

The variable time interval can be used to reject not only ghost objects,but to reject objects that exceed a fixed distance. For example, certainapplications may not want to process objects that exist at a distanceexceeding a fixed threshold (e.g., 150 meters). The variable timeinterval filtering algorithm can be used to verify that an object existsat a distance beyond the fixed threshold, and reject any ghost objectsmay stem from that object, but a system using the data obtained from thefiltering algorithm may reject objects verified to exist beyond thefixed threshold.

The high frequency, variable time interval filtering algorithm discussedherein is also able to take the following scenario into account. Assumethere is transparent object/small object in the range of c/2*M. Thetransparent object reflects certain partial of signal back to thereceiver, but the remainder of the transmission pulse keeps propagatingand hits a far object, which is out of the range of c/2*M. In addition,the distance between the near object and far object is exactly equal toc/2*M, which means the two objects overlapped.

In some embodiments, the LiDAR system is able to discriminate amongobserved objects that are relatively close and observed objects that arerelatively far by varying a time interval between successive laserpulses being emitted by the LiDAR system. Thus, by varying the timeinterval and using that as part of the basis for determining objectdistance calculations, the LiDAR system and methods for the use thereofcan differentiate among return pulses and accurately classify whetherthe return pulse corresponds to a close object, a far object, a ghostobject, or is derived from another laser source. If desired, the resultsof the discrimination can be used as data points for generating an imagerepresenting a field of view of the LiDAR system.

In some embodiments, LiDAR system can transmit laser pulses insuccession, such that a time interval between successively transmittedlaser pulses is varied. The LiDAR system can detect return pulses thatare consequences of the transmitted laser pulses. The LiDAR system canuse the varied time interval of successively transmitted laser pulses todiscriminate among distance calculations of an object corresponding tothe return pulses. This enables the LiDAR system to verify which one ofa relatively far distance calculation corresponding to an object and arelatively close distance calculation corresponding to the same objectis incorrect. This also enables the LiDAR system to reject distancecalculations corresponding to a ghost object and to reject return pulsesthat are the consequence of laser pulses originating from another lasertransmission source.

In some embodiments, the LiDAR system can transmit successivetransmission pulses in accordance with a variable time interval, whereinthe variable time interval changes for each transmission pulse, receivereturn pulses corresponding to an object, and determine distancecalculations corresponding to the object based, at least in part, on thereturn pulses. The LiDAR system can discriminate among the distancecalculations by evaluating the plurality of return pulses in connectionwith the variable time interval of the successive transmission pulses.If desired, the discriminated distances can be sued as data points togenerate an image representing a field of view of the LiDAR system.

FIG. 9 is a functional block diagram illustrating a vehicle system 900,according to an example embodiment. Vehicle 900 can be configured tooperate fully or partially in an autonomous mode. For example, vehicle900 can control itself while in the autonomous mode, and may be operableto determine a current state of the vehicle and its environment,determine a predicted behavior of at least one other vehicle in theenvironment, determine a confidence level that may correspond to alikelihood of the at least one other vehicle to perform the predictedbehavior, and control vehicle 900 based on the determined information.While in autonomous mode, the vehicle 900 may be configured to operatewithout human interaction.

In some embodiments, vehicle 900 can operate under solely control of ahuman operator, but the various sensors and systems of the vehicle andthe road conditions (e.g., road and the path traveled, other vehicles,stop signs, traffic lights, various events occurring outside of thevehicle) can be monitored and recorded.

Vehicle 900 can include various subsystems such as a propulsion system902, a sensor system 904, a control system 906, one or more peripherals908, as well as a power supply 910, a computer system 912, and a userinterface 916. Vehicle 900 may include more or fewer subsystems and eachsubsystem can include multiple elements. Further, each of the subsystemsand elements of vehicle 900 can be interconnected. Thus, one or more ofthe described functions of the vehicle 900 may be divided up intoadditional functional or physical components, or combined into fewerfunctional or physical components. In some further examples, additionalfunctional and/or physical components may be added to the examplesillustrated by FIG. 9.

Propulsion system 902 may include components operable to provide poweredmotion for the vehicle 900. Depending upon the embodiment, thepropulsion system 902 can include an engine/motor 918, an energy source919, a transmission 920, and wheels/tires 921. The engine/motor 918 canbe any combination of an internal combustion engine, an electric motor,steam engine, Stirling engine, or other types of engines and/or motors.In some embodiments, the engine/motor 918 may be configured to convertenergy source 919 into mechanical energy. In some embodiments, thepropulsion system 902 can include multiple types of engines and/ormotors. For instance, a gas-electric hybrid car can include a gasolineengine and an electric motor. Other examples are possible.

Energy source 919 can represent a source of energy that may, in full orin part, power the engine/motor 918. That is, the engine/motor 918 canbe configured to convert the energy source 919 into mechanical energy.Examples of energy sources 919 include gasoline, diesel, otherpetroleum-based fuels, propane, other compressed gas-based fuels,ethanol, solar panels, batteries, and other sources of electrical power.The energy source(s) 919 can additionally or alternatively include anycombination of fuel tanks, batteries, capacitors, and/or flywheels. Theenergy source 919 can also provide energy for other systems of thevehicle 900.

Transmission 920 can include elements that are operable to transmitmechanical power from the engine/motor 918 to the wheels/tires 921. Tothis end, the transmission 920 can include a gearbox, clutch,differential, and drive shafts. The transmission 920 can include otherelements.

The drive shafts can include one or more axles that can be coupled tothe one or more wheels/tires 921.

Wheels/tires 921 of vehicle 900 can be configured in various formats,including a unicycle, bicycle/motorcycle, tricycle, or car/truckfour-wheel format. Other wheel/tire geometries are possible, such asthose including six or more wheels. Any combination of the wheels/tires921 of vehicle 900 may be operable to rotate differentially with respectto other wheels/tires 921. The wheels/tires 921 can represent at leastone wheel that is fixedly attached to the transmission 920 and at leastone tire coupled to a rim of the wheel that can make contact with thedriving surface. The wheels/tires 921 can include any combination ofmetal and rubber, or another combination of materials.

Sensor system 904 may include a number of sensors configured to senseinformation about an environment of the vehicle 900. For example, thesensor system 904 can include a Global Positioning System (GPS) 922, aninertial measurement unit (IMU) 924, a RADAR unit 926, a laserrangefinder/LIDAR unit 928, and a camera 930. The sensor system 904 canalso include sensors configured to monitor internal systems of thevehicle 900 (e.g., 02 monitor, fuel gauge, engine oil temperature).Other sensors are possible as well.

One or more of the sensors included in sensor system 904 can beconfigured to be actuated separately and/or collectively in order tomodify a position and/or an orientation of the one or more sensors.

GPS 922 may be any sensor configured to estimate a geographic locationof the vehicle 900. To this end, GPS 922 can include a transceiveroperable to provide information regarding the position of the vehicle900 with respect to the Earth.

IMU 924 can include any combination of sensors (e.g., accelerometers andgyroscopes) configured to sense position and orientation changes of thevehicle 900 based on inertial acceleration.

RADAR unit 926 may represent a system that utilizes radio signals tosense objects within the local environment of the vehicle 900. In someembodiments, in addition to sensing the objects, the RADAR unit 926 mayadditionally be configured to sense the speed and/or heading of theobjects. Similarly, laser rangefinder or LIDAR unit 928 may be anysensor configured to sense objects in the environment in which thevehicle 900 is located using lasers. Depending upon the embodiment, thelaser rangefinder/LIDAR unit 928 can include one or more laser sources,a laser scanner, and one or more detectors, among other systemcomponents. The laser rangefinder/LIDAR unit 928 can be configured tooperate in a coherent (e.g., using heterodyne detection) or anincoherent detection mode.

Camera 930 can include one or more devices configured to capture aplurality of images of the environment of vehicle 900. Camera 930 can bea still camera or a video camera.

Control system 906 may be configured to control operation of vehicle 900and its components. Accordingly, control system 906 can include variouselements include steering unit 932, throttle 934, brake unit 936, asensor fusion algorithm 938, a computer vision system 940, anavigation/pathing system 942, and an obstacle avoidance system 944.

Steering unit 932 can represent any combination of mechanisms that maybe operable to adjust the heading of vehicle 900. Throttle 934 can beconfigured to control, for instance, the operating speed of theengine/motor 918 and, in turn, control the speed of the vehicle 900.Brake unit 936 can include any combination of mechanisms configured todecelerate the vehicle 900.

Brake unit 936 can use friction to slow wheels/tires 921. In otherembodiments, the brake unit 936 can convert the kinetic energy ofwheels/tires 921 to electric current. The brake unit 936 may take otherforms as well. The brake unit 936 may control braking of the vehicle900, for example, using a braking algorithm that takes into accountinput from one or more units of the sensor system 904.

Sensor fusion algorithm 938 may be an algorithm (or a computer programproduct storing an algorithm) configured to accept data from the sensorsystem 904 as an input. The data may include, for example, datarepresenting information sensed at the sensors of the sensor system 904.The sensor fusion algorithm 938 can include, for instance, a Kalmanfilter, Bayesian network, or other algorithm. The sensor fusionalgorithm 938 can further provide various assessments based on the datafrom sensor system 904. Depending upon the embodiment, the assessmentscan include evaluations of individual objects and/or features in theenvironment of vehicle 900, evaluation of a particular situation, and/orevaluate possible impacts based on the particular situation. Otherassessments are possible.

Computer vision system 940 may be any system operable to process andanalyze images captured by camera 930 in order to identify objectsand/or features in the environment of vehicle 900 that can includetraffic signals, road way boundaries, and obstacles. Computer visionsystem 940 can use an object recognition algorithm, a Structure FromMotion (SFM) algorithm, video tracking, and other computer visiontechniques. In some embodiments, the computer vision system 940 can beadditionally configured to map an environment, track objects, estimatethe speed of objects, etc.

Navigation and pathing system 942 may be any system configured todetermine a driving path for the vehicle 900, for example, byreferencing navigation data such as geographical or map data. Thenavigation and pathing system 942 may additionally be configured toupdate the driving path dynamically while the vehicle 900 is inoperation. In some embodiments, the navigation and pathing system 942can be configured to incorporate data from the sensor fusion algorithm938, the GPS 922, and one or more predetermined maps so as to determinethe driving path for vehicle 900. Obstacle avoidance system 944 canrepresent a control system configured to identify, evaluate, and avoidor otherwise negotiate potential obstacles in the environment of thevehicle 900. Control system 906 may additionally or alternativelyinclude components other than those shown and described.

Peripherals 908 may be configured to allow interaction between thevehicle 900 and external sensors, other vehicles, other computersystems, and/or a user. For example, peripherals 908 can include awireless communication system 946, a touchscreen 948, a microphone 950,and/or a speaker 952. In an example embodiment, peripherals 908 canprovide, for instance, means for a user of the vehicle 900 to interactwith the user interface 916. To this end, touchscreen 948 can provideinformation to a user of vehicle 900. User interface 916 can also beoperable to accept input from the user via the touchscreen 948. Thetouchscreen 948 may be configured to sense at least one of a positionand a movement of a user's finger via capacitive sensing, resistancesensing, or a surface acoustic wave process, among other possibilities.

Touchscreen 948 may be capable of sensing finger movement in a directionparallel or planar to the touchscreen surface, in a direction normal tothe touchscreen surface, or both, and may also be capable of sensing alevel of pressure applied to the touchscreen surface. Touchscreen 948may be formed of one or more translucent or transparent insulatinglayers and one or more translucent or transparent conducting layers.Touchscreen 948 may take other forms as well.

In other instances, peripherals 908 may provide means for the vehicle900 to communicate with devices within its environment. Microphone 950may be configured to receive audio (e.g., a voice command or other audioinput) from a user of vehicle 900. Similarly, speakers 952 may beconfigured to output audio to the user of vehicle 900.

In one example, wireless communication system 946 can be configured towirelessly communicate with one or more devices directly or via acommunication network. For example, wireless communication system 946can use 3G cellular communication, such as CDMA, EVDO, GSM/GPRS, or 4Gcellular communication, such as WiMAX or LTE. Alternatively, wirelesscommunication system 946 can communicate with a wireless local areanetwork (WLAN), for example, using WiFi. In some embodiments, wirelesscommunication system 946 can communicate directly with a device, forexample, using an infrared link, Bluetooth, or ZigBee. Other wirelessprotocols, such as various vehicular communication systems, are possiblewithin the context of the disclosure. For example, the wirelesscommunication system 946 can include one or more dedicated short rangecommunications (DSRC) devices that can include public and/or privatedata communications between vehicles and/or roadside stations.

Power supply 910 may provide power to various components of vehicle 900and can represent, for example, a rechargeable lithium-ion or lead-acidbattery. In some embodiments, one or more banks of such batteries can beconfigured to provide electrical power. Other power supply materials andconfigurations are possible. In some embodiments, the power supply 910and energy source 919 can be implemented together, as in someall-electric cars.

Many or all of the functions of vehicle 900 can be controlled bycomputer system 912. Computer system 912 may include at least oneprocessor 913 (which can include at least one microprocessor) thatexecutes instructions 915 stored in a non-transitory computer readablemedium, such as the data storage 914. Computer system 912 may alsorepresent a plurality of computing devices that may serve to controlindividual components or subsystems of the vehicle 900 in a distributedfashion.

In some embodiments, data storage 914 may contain instructions 915(e.g., program logic) executable by processor 913 to execute variousfunctions of vehicle 900, including those described above in connectionwith FIG. 9. In some embodiments, processor 913 may be operative to runan artificial intelligence (AI) engine, for example, to control thevarious systems of the vehicle 900. Data storage 914 may containadditional instructions as well, including instructions to transmit datato, receive data from, interact with, and/or control one or more ofpropulsion system 902, sensor system 904, control system 906, andperipherals 908. In addition to instructions 915, data storage 914 maystore data such as roadway maps, path information, among otherinformation. Such information may be used by vehicle 900 and computersystem 912 at during the operation of vehicle 900 in the autonomous,semi-autonomous, and/or manual modes.

Vehicle 900 may include a user interface 916 for providing informationto or receiving input from a user of vehicle 900. User interface 916 cancontrol or enable control of content and/or the layout of interactiveimages that can be displayed on the touchscreen 948. Further, userinterface 916 can include one or more input/output devices within theset of peripherals 908, such as wireless communication system 946,touchscreen 948, microphone 950, and the speaker 952.

Port 960 may be a port through which vehicle 900 receives power tocharge power supply 910 and to communicate data stored in data store914.

Computer system 912 may control the function of vehicle 900 based oninputs received from various subsystems (e.g., propulsion system 902,sensor system 104, and control system 906), as well as from userinterface 916. For example, computer system 912 may utilize input fromcontrol system 906 in order to control steering unit 932 to avoid anobstacle detected by sensor system 904 and obstacle avoidance system944. Depending upon the embodiment, computer system 912 can be operableto provide control over many aspects of vehicle 900 and its subsystems.

The components of vehicle 900 can be configured to work in aninterconnected fashion with other components within or outside theirrespective systems. For instance, in an example embodiment, camera 930can capture a plurality of images that can represent information about astate of an environment of vehicle 900 operating in an autonomous ormanual mode. The environment can include every conceivable type of datathat can be observed and collected by vehicle 900. For example, theenvironment can include the road and all aspects associated with theroad such as temperature, composition of the road (e.g., concrete orasphalt), moisture level, lanes, curbs, turn lanes, cross walks, stoplights, stop signs, yield signs and other traffic signs, and barricades.The environment can include objects such as other vehicles, people,random debris in or adjacent to the road.

Computer system 912 can monitor and log the environmental inputs inconjunction with operational states of the vehicle. The operationalstates can refer to operational and control parameters of the vehiclesuch as speed, trajectory, steering input, acceleration input, and brakeinput, and also can include results of driver input or AI driver input.This way, regardless of whether the vehicle is operating in autonomousmode or under human control, computer system 912 can simultaneously logthe environmental inputs and the operational states to provide acomprehensive vehicle log.

Although FIG. 9 shows various components of vehicle 900, i.e., wirelesscommunication system 946, computer system 912, data storage 914, anduser interface 916, as being integrated into vehicle 900, one or more ofthese components can be mounted or associated separately from thevehicle 900. For example, data storage 914 can, in part or in full,exist separate from vehicle 900. Thus, vehicle 900 can be provided inthe form of device elements that may be located separately or together.The device elements that make up vehicle 900 can be communicativelycoupled together in a wired and/or wireless fashion.

It is believed that the disclosure set forth herein encompasses multipledistinct inventions with independent utility. While each of theseinventions has been disclosed in its preferred form, the specificembodiments thereof as disclosed and illustrated herein are not to beconsidered in a limiting sense as numerous variations are possible. Eachexample defines an embodiment disclosed in the foregoing disclosure, butany one example does not necessarily encompass all features orcombinations that may be eventually claimed. Where the descriptionrecites “a” or “a first” element or the equivalent thereof, suchdescription includes one or more such elements, neither requiring norexcluding two or more such elements. Further, ordinal indicators, suchas first, second or third, for identified elements are used todistinguish between the elements, and do not indicate a required orlimited number of such elements, and do not indicate a particularposition or order of such elements unless otherwise specifically stated.

Moreover, any processes described with respect to FIGS. 1-9, as well asany other aspects of the invention, may each be implemented by software,but may also be implemented in hardware, firmware, or any combination ofsoftware, hardware, and firmware. They each may also be embodied asmachine- or computer-readable code recorded on a machine- orcomputer-readable medium. The computer-readable medium may be any datastorage device that can store data or instructions which can thereafterbe read by a computer system. Examples of the computer-readable mediummay include, but are not limited to, read-only memory, random-accessmemory, flash memory, CD-ROMs, DVDs, magnetic tape, and optical datastorage devices. The computer-readable medium can also be distributedover network-coupled computer systems so that the computer readable codeis stored and executed in a distributed fashion. For example, thecomputer-readable medium may be communicated from one electronicsubsystem or device to another electronic subsystem or device using anysuitable communications protocol.

The computer-readable medium may embody computer-readable code,instructions, data structures, program modules, or other data in amodulated data signal, such as a carrier wave or other transportmechanism, and may include any information delivery media. A modulateddata signal may be a signal that has one or more of its characteristicsset or changed in such a manner as to encode information in the signal.

It is to be understood that any or each module or state machinediscussed herein may be provided as a software construct, firmwareconstruct, one or more hardware components, or a combination thereof.For example, any one or more of the state machines or modules may bedescribed in the general context of computer-executable instructions,such as program modules, that may be executed by one or more computersor other devices. Generally, a program module may include one or moreroutines, programs, objects, components, and/or data structures that mayperform one or more particular tasks or that may implement one or moreparticular abstract data types. It is also to be understood that thenumber, configuration, functionality, and interconnection of the modulesor state machines are merely illustrative, and that the number,configuration, functionality, and interconnection of existing modulesmay be modified or omitted, additional modules may be added, and theinterconnection of certain modules may be altered.

Whereas many alterations and modifications of the present invention willno doubt become apparent to a person of ordinary skill in the art afterhaving read the foregoing description, it is to be understood that theparticular embodiments shown and described by way of illustration are inno way intended to be considered limiting. Therefore, reference to thedetails of the preferred embodiments is not intended to limit theirscope.

1-36. (canceled)
 37. A method, comprising: emitting, by a transmissionsystem of a light ranging and detection (LiDAR) system, a plurality oftransmission pulses using a plurality of variable time intervalscomprising a first time interval and a second time interval, wherein thefirst time interval and the second time interval are not equal;receiving, by a receiver, a plurality of return pulses; calculating, bya receiver control circuitry, a first plurality of object distances,wherein each of the first plurality of object distances corresponds toone of the plurality of return pulses and one of the plurality oftransmission pulses associated with the plurality of variable timeintervals; determining, by the receiver control circuitry, a secondplurality of object distances of a plurality of neighboring returnpulses; and determining, by the receiver control circuitry, whether thesecond plurality of object distances of the plurality of neighboringreturn pluses fails to meet one or more filter criteria by determining adistance comparison value based on the time intervals associated withthe plurality of transmission pulses, wherein the distance comparisonvalue corresponds to a likelihood or probability that the secondplurality of object distances of the plurality of neighboring returnpulses fails to meet the one or more filter criteria.
 38. The method ofclaim 37, wherein one or more of the first plurality of object distancesis calculated based on a most recently emitted transmission pulse or asecond most recently emitted transmission pulse.
 39. The method of claim37, wherein the plurality of variable time intervals further comprises athird time interval that is not equal to the first time interval or thesecond time interval.
 40. The method of claim 37, wherein each of theplurality of return pulses comprises light from one of the transmissionpulses that is reflected from an object located at a distance from theLiDAR system.
 41. The method of claim 37, wherein determining, by thereceiver control circuitry, the second plurality of object distances ofthe plurality of neighboring return pulses comprises: determining two ormore object distances associated with neighboring return pulses, whereinthe two or more object distances are calculated based on a most recentlyemitted transmission pulse or a second most recently emittedtransmission pulse.
 42. The method of claim 37, wherein each of thefirst plurality of object distance corresponds to one or more of (1)location information associated with a return pulse, the locationinformation comprising a calculated distance to the LiDAR system, (2)the time interval associated with successive transmission pulses, and(3) filter information for the object distance.
 43. The method of claim37, further comprising: determining an object distance of the firstplurality of object distances corresponding to a return pulse, thereturn pulses being detected a time difference after emission of acorresponding most recently emitted transmission pulse, wherein the timedifference is less than the time interval between the most recentlyemitted transmission pulse and the second most recently emittedtransmission pulse.
 44. The method of claim 43, wherein the objectdistance OD is determined from an expression OD=c·ΔT/2, wherein c is aspeed of light.
 45. The method of claim 37, wherein determining whetherthe second plurality of object distances of the plurality of neighboringreturn pluses fails to meet one or more filter criteria comprises:determining that the second plurality of object distances of theplurality of neighboring return pluses fails to meet the one or morefilter criteria by determining that the distance comparison value isgreater than a threshold value.
 46. The method of claim 37, whereindetermining whether the second plurality of object distances of theplurality of neighboring return pluses fails to meet one or more filtercriteria comprises: determining that the second plurality of objectdistances of the plurality of neighboring return pluses fails to meetthe one or more filter criteria when the distance comparison value isgreater than a particular threshold value.
 47. The method of claim 37,further comprising: in response to determining that the second pluralityof object distances of the plurality of neighboring return pluses failsto meet the one or more filter criteria, performing at least one of:labeling the second plurality of object distances as negative; orrejecting the second plurality of object distances.
 48. A method,comprising: emitting, by a light source of a light ranging and detection(LiDAR) system, a plurality of optical pulses using a plurality ofvarying repetition rates corresponding to a first time interval and asecond time interval, wherein the first time interval and the secondtime interval are not equal; detecting, by a receiver of the LiDARsystem, a plurality of return optical pulses; generating, by a processorof the LiDAR system, a plurality of data elements, wherein each of theplurality of data elements corresponds to one of the plurality of returnoptical pulses and wherein each of the plurality of data elementcorresponds to a repetition rate associated with a most recently emittedoptical pulse of the plurality of optical pulses; determining, by theprocessor, a group of neighboring data elements of the plurality of dataelements; and determining, by the processor, whether a data element ofthe group of neighboring data elements has a range ambiguity bydetermining a data element difference value based on the repetition rateassociated with each data element of the group of neighboring dataelements, wherein the data element difference value corresponds to alikelihood or probability that the data element of the group ofneighboring data elements is caused by the range ambiguity.
 49. Themethod of claim 48, wherein each of the plurality of data elementscorresponds to a repetition rate associated with a most recently emittedoptical pulse or second most recently emitted optical pulse.
 50. Themethod of claim 48, wherein the plurality of varying repetition ratesfurther corresponds to a third time interval that is not equal to thefirst time interval or the second time interval.
 51. The method of claim48, wherein each of the return optical pulses comprises light from oneof the optical pulses that is scattered by a target located at adistance from the LiDAR system.
 52. The method of claim 48, whereindetermining, by the processor, the group of neighboring data elementscomprises determining one or more data elements from the plurality ofdata elements that are located within a threshold distance from eachother.
 53. The method of claim 48, wherein each data element comprisesone or more of (1) location information associated with the dataelement, (2) the repetition rate associated with the most recentlyemitted optical pulse, and (3) range ambiguity information for the dataelement.
 54. The method of claim 48, further comprising: determining adistance associated with a data element corresponding to a returnoptical pulse, the return optical pulse being detected a time differenceΔT after emission of a corresponding most recently optical pulse,wherein the time difference ΔT is less than the time interval betweenthe most recently emitted optical pulse and the second most recentlyemitted transmission pulse.
 55. The method of claim 54, wherein the dataelement distance OD is determined from an expression OD=c·ΔT/2, whereinc is a speed of light.
 56. The method of claim 48, wherein determiningthat a data element of the group of neighboring data elements has arange ambiguity comprises determining that the data element differencevalue is greater than a threshold value.
 57. The method of claim 48,wherein the processor is configured to determine that a data element ofthe group of neighboring data elements has a range ambiguity comprisesdetermining when the data element difference value is greater than aparticular threshold value.
 58. The method of claim 48, furthercomprising: in response to determining that a data element of the groupof neighboring data elements has a range ambiguity, performing one of:tagging the data element with a value that corresponds to the likelihoodor probability that the data element has range ambiguity; or discardingor ignoring the data element
 59. A light detection and ranging (LiDAR)system, comprising: a laser transmission source operative to transmitlaser pulses in succession, wherein time intervals between successivelytransmitted laser pulses are varied; a receiver system operative todetect return pulses that are consequences of the transmitted laserpulses; and control circuitry operative to use the varied time intervalsof the successively transmitted laser pulses to discriminate amongdistance calculations of an object corresponding to the return pulses.60. The LiDAR system of claim 59, wherein the distance calculationscomprise a first distance calculation and a second distance calculation,the first distance calculation being greater than the second distancecalculation, and wherein the control circuitry is operative to verifywhich one of the first distance calculation and the second distancecalculation should be filtered out.
 61. The LiDAR system of claim 59,wherein the control circuitry is operative to discriminate among thedistance calculations of the object corresponding to the return pulsesby performing at least one of: rejecting distance calculationscorresponding to a ghost object; or rejecting return pulses that are theconsequence of laser pulses originating from another laser transmissionsource.
 62. A method for using a LiDAR system, comprising: transmittingsuccessive transmission pulses in accordance with variable timeintervals, wherein the variable time intervals change for a plurality ofthe successive transmission pulses; receiving a plurality of returnpulses corresponding to an object; determining distance calculationscorresponding to the object based on the plurality of return pulses anda plurality of the successive transmission pulses; discriminating amongthe distance calculations by evaluating the plurality of return pulsesin connection with the variable time intervals of the successivetransmission pulses; and providing the discriminated distancecalculations—as data points for generating an image representing a fieldof view of the LiDAR system
 63. The method of claim 62, wherein thedistance calculations comprise a first distance calculation and a seconddistance calculation, the first distance calculation being greater thanthe second distance calculation, and wherein the discriminating amongthe distance calculations comprises verifying which one of the firstdistance calculation and the second distance calculation should befileted out.
 64. The method of claim 62, wherein the discriminatingamong the distance calculations comprises at least one of: rejectingdistance calculations corresponding to a ghost object; or rejectingreturn pulses that are the consequence of laser pulses originating fromanother laser transmission source.
 65. The method of claim 62, whereinthe discriminating among the distance calculations comprises comparingat least two distance calculations corresponding to a currently detectedreturn pulse to at least two distance calculations corresponding to apreviously detected return pulse to filter out distance calculationsthat fail filter criteria.